Bayesian inference for exponential random graphs - POSTPONED DUE TO TRAVEL DIFFICULTIES
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If you have a question about this talk, please contact Rachel Fogg.
The exponential random graph is widely used in the statistical analysis of network data. It is a Markov random field model, and suffers from the problem that the likelihood is unavailable for all but trivially small networks.
This talk will present two approaches; one simulation based, the other deterministic, which aim to overcome this difficulty.
This talk is part of the Signal Processing and Communications Lab Seminars series.
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